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May 8 – 12, 2023
Norfolk Waterside Marriott
US/Eastern timezone

Optimizing Geant4 Hadronic Model Parameters Through Global Fits to Thin Target Data

May 9, 2023, 5:45 PM
Hampton Roads Ballroom VI (Norfolk Waterside Marriott)

Hampton Roads Ballroom VI

Norfolk Waterside Marriott

235 East Main Street Norfolk, VA 23510
Oral Track 3 - Offline Computing Track 3 - Offline Computing


Yarba, Julia (Fermi National Accelerator Laboratory)


Geant4, the leading detector simulation toolkit used in High Energy Physics, employs a set of physics models to simulate interactions of particles with matter across a wide range of interaction energies. These models, especially the hadronic ones, rely largely on directly measured cross-sections and inclusive characteristics, and use physically motivated parameters. However, they generally aim to cover a very wide range of possible simulation tasks and may not always be optimized for a particular process or a given material.
The Geant4 collaboration recently made many parameters of the models accessible via a configuration interface. This opens a possibility to fit simulated distributions to thin target experimental datasets and extract optimal values of the model parameters and the associated uncertainties. Such efforts are currently undertaken by the Geant4 Collaboration with the goal of offering alternative sets of model parameters, aka “tunes”, for certain applications. The efforts should subsequently lead to more accurate estimates of the systematic errors in physics measurements given the detector simulation role in performing the physics measurements.
Results from the study will be presented to illustrate how Geant4 model parameters can be optimized through applying fitting techniques, to improve the agreement between the Geant4 and the experimental data.

Keywords: Geant4 toolkit, hadronic interactions, optimizations of phenomenological models, fitting technique

Consider for long presentation Yes

Primary authors

Yarba, Julia (Fermi National Accelerator Laboratory) Dr Genser, Krzysztof (Fermilab) Jun, Soon Yung (Fermilab) Ribon, Alberto (CERN) Uzhinsky, Vladimir (JINR)

Presentation materials

Peer reviewing